Assessment of Risk Factors for Low Birth weight of Infants in Zanjan Province Using Quantile Regression Analysis

نویسندگان

  • asghar Marzban Zanjan University of Medical Sciences
  • mansor Sadeghzadeh MD, Dept. of Pediatrics, Assistant Professor, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
  • nima motamed MD. Dept. of Health Care Management, Zanjan Social Health Research Center, Zanjan University of Medical Sciences, Zanjan, Iran
چکیده مقاله:

Background: Low birth weight is one of the key indicators to assess the health of infants, and appropriate birth weight is one of the most important goals of any health system which also reflects the quality of prenatal care. Objectives: The present research aimed to study some of the factors associated with low birth weight using quantile regression analysis. Methods: A cross-sectional study was carried out on 621 infants born weighing less than 2500 grams in the period 2012-2013. The data were collected from the medical records of infants in health care centers of Zanjan Province which were selected based on multi-stage cluster sampling. The obtained data were statistically analyzed using quantile and multiple regression analysis in SAS-9.2. Results: In this study, 320 infants (51.5%) were female, and the mean age of mothers and the mean weight of infants were 27.1±5.8 years and 2236±299 grams, respectively. The results showed that low birth weight is significantly related to age, educational attainment, and the number of children. In addition, there was a significant relationship between infant weight and maternal age only in the tenth percentile (P=0.007), while such a relationship was not found in the higher percentiles (50 and 90) (P=0.0, 953.585). Conclusion: Some of the demographics of mothers such as educational attainment and gestational age were influential in the low birth weight of infants. Maternal age and birth weight were not statistically significant in all areas.

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assessment of risk factors for low birth weight of infants in zanjan province using quantile regression analysis

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عنوان ژورنال

دوره 6  شماره 4

صفحات  9- 14

تاریخ انتشار 2017-03

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